Does Income Matter? Study of Life Expectancy Across the World

In this report, we take a quick look at the how life expectancy differs between rich and poor countries, and display some of the new interactive data discovery tools we have been working on.

Gender differences in life expectancy at birth

Using the 2015 WDI indicators as the most recent full snapshot of the world economy.

The red dotted line shows an ideal situation of gender parity, where males and females would have an equal life expectancy. Members of both genders would be expected to live for the same amount of time, e.g. 70 years for males (x-axis) and females (y-axis).

The point sizes vary to reflect differences in populations of these countries.

We extracted several insights from the data and its visualization:

• Women do live longer than men everywhere except Swaziland. The country suffers from the lowest life expectancy in the world. The trend with female life expectancy dropping below the male indicator hit a low in 2004 and is potentially related to HIV situation in Swaziland. Explore the time trends further in this line graph.

• Low and lower middle income countries are grouped in the lower left quadrant. This proves that people in developing economies live shorter than in rich countries. Interestingly, the gender gap in life expectancy in developing countries is smaller than that of wealthier countries. In very simple terms, if you are poor you will live a shorter life in any case. Being born female would not provide you with a major extension of the length of your life. Among others, this contrasts sharply with situation in Russia, an upper middle income country. The gender differences reach 11+ years there due to alcohol and tobacco policy shortcomings.

• It is unusual to see an upper middle income and a high income country among low income countries at the [55;60] mark. In this case, the two countries with abnormally low life expectancies are South Africa and Equatorial Guinea. The latter is a curious example of a resource curse. It is classified as a high income country due to high GNI per capita caused by the presence of oil resources (read more about groupings of economies here).

To explore these and other cases use zoom and panning in the interactive chart below.

This information provides important context for development professionals. Whether an economist or a policymaker, both can put it to use in the context of their work. Moving forward with this topic, we recommend augmenting the analysis by looking at life expectancy at age 65, similar to the analysis in this paper.

The World Bank staff are here to facilitate the access to development information. In future blog posts, we will be updating our dataviz catalog with new products. If you are interested in exploring development data and downloading it for further analysis, visit World Bank Data to learn more.

Reproducible research: download RMarkdown file.